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      "source": [
        "%matplotlib inline"
      ]
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      "source": [
        "\n# Compact estimator representations\n\n\nThis example illustrates the use of the print_changed_only global parameter.\n\nSetting print_changed_only to True will alterate the representation of\nestimators to only show the parameters that have been set to non-default\nvalues. This can be used to have more compact representations.\n\n"
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    {
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      "execution_count": null,
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      "source": [
        "print(__doc__)\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn import set_config\n\n\nlr = LogisticRegression(penalty='l1')\nprint('Default representation:')\nprint(lr)\n# LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n#                    intercept_scaling=1, l1_ratio=None, max_iter=100,\n#                    multi_class='auto', n_jobs=None, penalty='l1',\n#                    random_state=None, solver='warn', tol=0.0001, verbose=0,\n#                    warm_start=False)\n\nset_config(print_changed_only=True)\nprint('\\nWith changed_only option:')\nprint(lr)\n# LogisticRegression(penalty='l1')"
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